How to optimize your search using query suggestions
In our previous videos we learnt how to use the visual approach to create the correct structure for our search strategy. In this video, we’ll look at techniques to create the right content.
A key task in developing effective search strategies is choosing the right keywords. But how do we create these terms in the first place? One way is simply to brainstorm them, i.e. think up related terms for each facet. Or you might use your search results as a source of inspiration. But is there a more efficient way to generate related terms?
Well with 2Dsearch, it turns out there is. If you right click on a term, you see an option to ‘Suggest terms’. This invokes a call to our language processing API, which looks up the term in a variety of knowledge based resources and machine-learning models. For example, if you are currently seeking generic results via a search engine like Bing, then query suggestions are drawn from DBPedia and our own deep learning language model. Alternatively, if you are targeting biomedical or life sciences sources via Pubmed, then the suggestions are drawn from Mesh and our own language model.
To add a suggested term, simply select it and click Add Selected Terms. The key thing about these suggestions is that not only are they highly relevant to your original term, but they are automatically added within your chosen facet. Moreover, you can continue to generate terms using this approach. Note that as you add terms the results are always updating in real time.
Query suggestions are useful for most people, but particularly those whose native language is not English. It is difficult to think of related terms, let alone know whether they are true synonyms or not. 2Dsearch’s query suggestions solve that problem.